prospective postdocs and PhD studentswho are willing to apply for a European or Belgian fellowship with me.

a Teaching Assistant (TA) who has a solid background in Chemistry and is fluent in Dutch (Nederlands) (demonstrable CEFR proficiency level B2 or better required for non-native speakers). This job consists for almost 40% out of teaching and for the remaining ≥60% out of research towards a PhD. Follow this link (in Dutch) for more details!

Present Research

Empirical force fields20 are presently the only computational methods fast enough to routinely perform molecular dynamics simulations of large chemical systems, such as proteins, on relevant time scales. The CHARMM force field is widely used for simulating biomolecular systems, being capable of representing proteins, nucleic acids, lipids and carbohydrates.22 The CHARMM General Force Field (CGenFF) adds to this a wide range of chemical groups present in biomolecules and drug-like molecules including a large number of heterocyclic scaffolds. CGenFF thus makes it possible to perform "all-CHARM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems. As a validation, CGenFF was shown to accurately reproduce geometric, vibrational and energetic data, including interactions with water, as well as satisfactorily reproducing the experimental molecular volumes for 111 pure solvents and heats of vaporization of 95 molecules.9
The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. This is testified by our tutorials that take the reader through the parametrization process in a step-by-step fashion.

Following the first release of CGenFF, significant improvements in the force field's coverage of chemical space have been made15,29 and virtual particles were introduced to better capture halogen bonds.31 In parallel, the CGenFF program was developed. This program performs atom typing and assignment of parameters and charges by analogy in a fully automated fashion. The atom typer is deterministic and based on a programmable decision tree, making it easy to implement complex atom typing rules and to update the atom typing scheme as the force field grows.16 Assignment of bonded parameters is based on substituting atom types in the definition of the desired parameter. A penalty is associated with every substitution and the existing parameter with the lowest total penalty is chosen as an approximation for the desired parameter; the "penalty score" is returned to the user as a measure for the accuracy of the approximation. Charges are assigned using an extended bond-charge increment scheme that is able to capture short- and medium-range inductive and mesomeric effects.17

Automatic fitting of Molecular Mechanics parameters

Automated methods for force field parametrization have attracted renewed interest of the community, but the robustness issues associated with the often ill-conditioned nature of parameter optimization have been vastly underappreciated in the recent literature. We developed a Linear Least Squares (LLS) procedure that is able to simultaneously fit all the bonded parameters in a Class I force field and includes a novel restraining strategy that overcomes robustness issues in the LLS fitting of bonded parameters while minimally impacting the fitted values of well-behaved parameters.26 The same procedure was also used for the fitting of the bond-charge increments in the next release of the CGenFF program, illustrating the method's potential for robustly solving general LLS problems beyond force field parametrization. The fitting part of the methodology was implemented in a C program named "lsfitpar" is available to the community under the Affero GPL. It hoped it will become an important part of the sprawling ecosystem of automatic parametrization interfaces. Future directions include further automation, validation of the methodology for the purpose of charge fitting, testing of its ability to use Monte Carlo conformational sampling data and extending the program's feature set.

Mimetics of secondary structure elements in proteins

My first contact with peptidomimetics mimicking specific secondary structure motifs was in the Dirk Tourwé lab, where this was a major research topic, and where I assisted in conformational studies aimed at determining the β-turn propensity of 4-Amino-1,2,4,5-tetrahydro-2-benzazepin-3-ones and derivatives.5 Several years later, when working in the MacKerell lab, I became involved in Steven Fletcher's research on α-helix and β-sheet mimetics. In this context, I assisted in the design of oligoamide-foldamer-based α-helix mimetics that target the interaction of the BCL-xL oncoprotein with the pro-apoptotic BAK protein,13,18 as well as the design of a 1,2-diphenylacetylene-based scaffold for amphipathic α-helix mimetics with potential applications in binding the Mcl-1 oncoprotein.19 Work on a β-sheet mimetic with therapeutic potential against cancer through a different mechanism is also in progress.

Inhibition of the BCL6/SMRT interaction

This project is a collaborative effort involving the Molecular Biology group of Ari Melnick, the X-ray Crystallography and Structural Biology group of Gil Privé, the Organic Chemistry group of Andy Coop and Alex MacKerell's CADD center. The aim of this collaboration is to develop novel anti-cancer drugs that target the BCL6 oncogenic transcriptional repressor. As part of Alex MacKerell's group, my role consists mainly of assisting in the discovery of new leads by means of in silico screening of libraries of commercially available compounds. In this context, we employ both ligand-based and structure-based drug design strategies. In other words, we identify new leads by their chemical homology to known inhibitors as well as their binding affinity to relevant parts of BCL6, as predicted by docking studies.30

Past Research

Post-HF and post-DFT evaluation of the dispersion energy

Dispersion interactions play a fundamental role in physics, chemistry and biology, where they appear, for example, in π-π stacking interactions contributing to the structure, catalysis and inhibition, of proteins. Therefore, a theoretical description of these interactions would be desirable. This is not easily accomplished because dispersion interactions can only be described at a level of theory that includes electron correlation. Since current Density Functional Theory (DFT) methods do not correctly reproduce disperion interactions, at least second order Møller-Plesset (MP2) theory must be used. However, systems with a biologically relevant size are currently far beyond the computational reach of this method. Therefore, our goal is to include a "semi-empirical" dispersion correction on top of the DFT energy. This is accomplished by combining a recent approximation scheme by Becke and Johnson with a Hirschfeld-type scheme for partitioning molecular polarizabilities into atomic contributions.7,8,10,12

Cyberenvironment for MM and SE parameter optimization

The ParamChem project (full title: "Extensible Cyberenvironments for Empirical and Semiempirical Hamiltonian Parameter Optimization and Dissemination") is an NSF sponsored initiative to develop an integrated cyber environment to address the simulation needs of molecular sciences. The proposed infrastructure will provide reference data organizers and generators as well as workflows for automatic parameterization of Molecular Mechanics (MM) Force Fields as well as Semi-Empirical (SE) methods. A comprehensive utility for the optimization and testing of parameters in Force Fields and Semi-Empirical models will be set up, allowing experts in these fields to develop novel models of higher accuracy in shorter time periods. These models can then be made available to the computational chemistry community at large via a parameter database. This will make it easier for computational chemists to find an appropriate model for the system they are studying, and, if necessary, to extend the model to novel functional groups using automated utilities. Currently, we're working on automatic force field parameterization in the context of CGenFF. In the long run, many other Molecular Mechanics as well as Semi-Empirical models will be integrated. From this, a wide range of parameters encompassing biological, organic and inorganic species will be accessible for direct use or further optimization.